Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Gagolewski, Marek"'
Inequality is an inherent part of our lives: we see it in the distribution of incomes, talents, resources, and citations, amongst many others. Its intensity varies across different environments: from relatively evenly distributed ones, to where a sma
Externí odkaz:
http://arxiv.org/abs/2304.07479
Publikováno v:
Journal of Informetrics 18(2), 2024, 101499
We introduce an iterative discrete information production process where we can extend ordered normalised vectors by new elements based on a simple affine transformation, while preserving the predefined level of inequality, G, as measured by the Gini
Externí odkaz:
http://arxiv.org/abs/2304.07480
Community detection is a critical challenge in analysing real graphs, including social, transportation, citation, cybersecurity, and many other networks. This article proposes three new, general, hierarchical frameworks to deal with this task. The in
Externí odkaz:
http://arxiv.org/abs/2303.12212
Publikováno v:
Fuzzy Sets and Systems 473, 108740, 2023
Agglomerative hierarchical clustering based on Ordered Weighted Averaging (OWA) operators not only generalises the single, complete, and average linkages, but also includes intercluster distances based on a few nearest or farthest neighbours, trimmed
Externí odkaz:
http://arxiv.org/abs/2303.05683
Publikováno v:
Journal of Classification, 2024
Minimum spanning trees (MSTs) provide a convenient representation of datasets in numerous pattern recognition activities. Moreover, they are relatively fast to compute. In this paper, we quantify the extent to which they are meaningful in low-dimensi
Externí odkaz:
http://arxiv.org/abs/2303.05679
Autor:
Gagolewski, Marek
Publikováno v:
Zenodo, Melbourne, ISBN: 978-0-6455719-2-9 (2024) https://deepr.gagolewski.com/
Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambitious students, professionals, and researchers with the knowledge and skills to become independent users of th
Externí odkaz:
http://arxiv.org/abs/2301.01188
Autor:
Gagolewski, Marek
Minimalist Data Wrangling with Python is envisaged as a student's first introduction to data science, providing a high-level overview as well as discussing key concepts in detail. We explore methods for cleaning data gathered from different sources,
Externí odkaz:
http://arxiv.org/abs/2211.04630
Autor:
Gagolewski, Marek
Publikováno v:
SoftwareX 20 (2022) 101270
The evaluation of clustering algorithms can involve running them on a variety of benchmark problems, and comparing their outputs to the reference, ground-truth groupings provided by experts. Unfortunately, many research papers and graduate theses con
Externí odkaz:
http://arxiv.org/abs/2209.09493
Publikováno v:
Information Sciences 363, 8-23, 2016
The time needed to apply a hierarchical clustering algorithm is most often dominated by the number of computations of a pairwise dissimilarity measure. Such a constraint, for larger data sets, puts at a disadvantage the use of all the classical linka
Externí odkaz:
http://arxiv.org/abs/2209.05757
Autor:
Gagolewski, Marek
Publikováno v:
Journal of Classification, 2024
There is no, nor will there ever be, single best clustering algorithm. Nevertheless, we would still like to be able to distinguish between methods that work well on certain task types and those that systematically underperform. Clustering algorithms
Externí odkaz:
http://arxiv.org/abs/2209.02935